Attack Detection Algorithm Based on Rossle Chaotic Average Mutual Information Feature Mining

2016 ◽  
Author(s):  
Guest Editor Jianping Du
Keyword(s):  
Mutual Information ◽  
Detection Algorithm ◽  
Attack Detection ◽  
Average Mutual Information ◽  
Feature Mining

Capacity Analysis for Correlated Multi-Hop MIMO Channels under Colored Noise

2015 ◽  
Vol 1 ◽  
pp. 41
Author(s):  
Nguyen N. Tran ◽  
Ha X. Nguyen
Keyword(s):  
Computational Complexity ◽  
Mutual Information ◽  
Closed Form Solution ◽  
Optimal Solution ◽  
Form Solution ◽  
Maximization Problem ◽  
Capacity Analysis ◽  
Mimo Channels ◽  
Average Mutual Information ◽  
Channel Output

A capacity analysis for generally correlated wireless multi-hop multi-input multi-output (MIMO) channels is presented in this paper. The channel at each hop is spatially correlated, the source symbols are mutually correlated, and the additive Gaussian noises are colored. First, by invoking Karush-Kuhn-Tucker condition for the optimality of convex programming, we derive the optimal source symbol covariance for the maximum mutual information between the channel input and the channel output when having the full knowledge of channel at the transmitter. Secondly, we formulate the average mutual information maximization problem when having only the channel statistics at the transmitter. Since this problem is almost impossible to be solved analytically, the numerical interior-point-method is employed to obtain the optimal solution. Furthermore, to reduce the computational complexity, an asymptotic closed-form solution is derived by maximizing an upper bound of the objective function. Simulation results show that the average mutual information obtained by the asymptotic design is very closed to that obtained by the optimal design, while saving a huge computational complexity.

Structural Design of Intrusion Detection System

2014 ◽  
Vol 530-531 ◽  
pp. 705-708
Author(s):  
Yao Meng
Keyword(s):  
Intrusion Detection ◽  
Structural Design ◽  
Intrusion Detection System ◽  
Detection System ◽  
Algorithm Design ◽  
Detection Algorithm ◽  
Attack Detection ◽  
Detection Algorithms ◽  
Defense Systems ◽  
Ddos Attack Detection

This paper first engine starting defense from Intrusion Detection, Intrusion detection engine analyzes the hardware platform, the overall structure of the technology and the design of the overall structure of the plug, which on the whole structure from intrusion defense systems were designed; then described in detail improved DDOS attack detection algorithm design thesis, and the design of anomaly detection algorithms.

scholarly journals Bayes-based ARP attack detection algorithm for cloud centers

2016 ◽  
Vol 21 (1) ◽  
pp. 17-28 ◽  
Author(s):  
Huan Ma ◽  
Hao Ding ◽  
Yang Yang ◽  
Zhenqiang Mi ◽  
James Yifei Yang ◽  
...  
Keyword(s):  
Detection Algorithm ◽  
Attack Detection

Input Vector Identification and System Model Construction by Average Mutual Information

2000 ◽  
Author(s):  
Paul B. Deignan ◽  
Peter H. Meckl ◽  
Matthew A. Franchek ◽  
Salim A. Jaliwala ◽  
George G. Zhu
Keyword(s):  
Mutual Information ◽  
System Model ◽  
Input Output ◽  
Output Data ◽  
Average Mutual Information ◽  
Virtual Sensors ◽  
Input Signals ◽  
Model Independent ◽  
Intelligent Model ◽  
Selection Of

Abstract A methodology for the intelligent, model-independent selection of an appropriate set of input signals for the system identification of an unknown process is demonstrated. In modeling this process, it is shown that the terms of a simple nonlinear polynomial model may also be determined through the analysis of the average mutual information between inputs and the output. Average mutual information can be thought of as a nonlinear correlation coefficient and can be calculated from input/output data alone. The methodology described here is especially applicable to the development of virtual sensors.

scholarly journals Event-triggered attack detection and identification in power-electronics-based DC microgrid

2021 ◽  
Author(s):  
Sicheng Gong
Keyword(s):  
Power Flow ◽  
Detection Algorithm ◽  
Power Line ◽  
Current Data ◽  
Attack Detection ◽  
Dc Microgrid ◽  
Detection Mechanism ◽  
Detection And Identification ◽  
Event Triggered ◽  
Identification Strategy

This paper proposes a novel event-triggered attack detection mechanism for converter-based DC microgrid system. Under a distributive network framework, each node collects its neighbours' relative data to regulate its own output for local stabilization. Without power line current data, hardly can an agent directly identify the source of unexpected power flow, especially under an organized attack composed of voltage variations and corresponding deceptive messages. In order to recognize traitors who broadcast wrong data, target at system distortion and even splitting, an efficient attack detection and identification strategy is mandatory. After the attack detector is triggered, each relative agent refuses to trust any received data directly before authentication. Through proposed two-step verification by comparing theoretical estimated signals with received ones, both self sensors and neighbour nodes would be inspected, and the attacker was difficult to hide himself. Through simulation on SIMULINK/PLECS and hardware experiments on dSpace Platform, the effectiveness of proposed detection algorithm has been proved.

scholarly journals Research on Pseudo-Node Detection Algorithm in Wireless Sensor Networks

2017 ◽  
Vol 13 (03) ◽  
pp. 113
Author(s):  
Wenjin Yu ◽  
Yong Li ◽  
Yuangeng Xu
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Sensor Network ◽  
Detection Algorithm ◽  
Comprehensive Analysis ◽  
Attack Detection ◽  
Wireless Sensor ◽  
Font Size ◽  
Simulation Results ◽  
Sensor Security

<span style="font-family: 'Times New Roman',serif; font-size: 12pt; mso-fareast-font-family: SimSun; mso-fareast-theme-font: minor-fareast; mso-ansi-language: EN-US; mso-fareast-language: ZH-CN; mso-bidi-language: AR-SA;">With the wide application of the wireless sensor network, the security of the sensor network is becoming increasingly important. In this paper, based on node ranging, a new intrusion node detection algorithm has been proposed for external pseudo-node detection in wireless sensor networks. The presence of the nodes under copying-attack and the pseudo-nodes in the network can be detected through inter-node ranging with appropriate use of various sensors of nodes themselves and comprehensive analysis of ranging results. Operating in a stand-alone or embedded manner, this method has remedied the defects in the traditional principle of attack detection. The simulation results show that the proposed method has excellent applicability in wireless sensor security detection.</span>

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